The famous mathematical psychologist Amos Tversky once said, “My colleagues, they study artificial intelligence; me, I study natural stupidity. ” The “stupidity” Tversky refers to is our inability to recognize that we are helpless against the biases that are hardwired into our brains. These biases affect us most in the decisions that we make on a daily basis. It therefore follows that these biases play a major role in Hotel Pricing and Revenue Management.
In the absence of collaborative data analysis, decisions made under uncertainty become highly subjective activities. The most relevant example in Hotel Revenue Management is the process of selecting the rate that has the best chance of optimizing revenue for any given night. In the vast majority of properties, this task remains a highly judgmental exercise. Even in properties that claim to use a “scientific” approach, the analysis applied is mostly algebraic or dependent on some “rule-of-thumb” set, which means that the effects of variance or “chance” are not being properly quantified to make a truly informed decision.
Revenue Managers must be keenly aware that any RM decision done without a thorough analytical interpretation of what is actually happening is likely to be subject to the unintentional application of some very human, but very dangerous biases. I thought it would be useful to highlight my list of the 10 most common biases applied in RM.
1. Confirmation bias (i.e. wishful thinking) is the tendency of people to favor information that confirms their beliefs. For example, we focus on spikes in the booking pattern that seem to verify our guesstimate of where the final occupancy will end up or how the month will close. These spikes may, in fact, be statistically insignificant.
2. Ambiguity bias is the tendency to avoid options for which we have little experience. This is often seen in the reluctance of some hotels to charge a rate that is outside of a defined “comfort” range. For some, this range may be defined by always staying below a certain competitor or within a percentage of the rates charged the previous year.
